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This new edition is a concise introduction to the basic methods of computational physics. Readers will discover the benefits of numerical methods for solving complex mathematical problems and for the direct simulation of physical processes.
The book is divided into two main parts: Deterministic methods and stochastic methods in computational physics. Based on concrete problems, the first part discusses numerical differentiation and integration, as well as the treatment of ordinary differential equations. This is extended by a brief introduction to the numerics of partial differential equations. The second part deals with the generation of random numbers, summarizes the basics of stochastics, and subsequently introduces Monte-Carlo (MC) methods. Specific emphasis is on MARKOV chain MC algorithms. The final two chapters discuss data analysis and stochastic optimization. All this is again motivated and augmented by applications from physics. In addition, the book offers a number of appendices to provide the reader with information on topics not discussed in the main text.
Numerous problems with worked-out solutions, chapter introductions and summaries, together with a clear and application-oriented style support the reader. Ready to use C++ codes are provided online.
"synopsis" may belong to another edition of this title.
About the Author:
Ewald Schachinger is a Professor in the Institute for Theoretical and Computational Physics in Graz University of Technology, Austria.
Benjamin A. Stickler is a Professor in the Institute of Theoretical Physics at the University of Duisburg-Essen, Germany.
Review:
Benjamin A. Stickler is a Professor in the Institute of Theoretical Physics at the University of Duisburg-Essen, Germany.
From the reviews:
“The authors characterize the aim of their book to ‘address the scenarios of direct simulation of physical processes and the solution of complex mathematical problems on a very basic level’. It is directed to lecturers teaching basic courses in Computational Physics and to students as a companion when starting studying in this field.” (Rolf Dieter Grigorieff, zbMATH, Vol. 1287, 2014)"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date2016
- ISBN 10 3319272632
- ISBN 13 9783319272634
- BindingHardcover
- Edition number2
- Number of pages425
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Book Description Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This new edition is a concise introduction to the basic methods of computational physics. Readerswill discover the benefits of numerical methods for solving complex mathematical problems and for thedirect simulation of physical processes. The book is divided into two main parts: Deterministic methods and stochastic methods in computationalphysics. Based on concrete problems, the first part discusses numerical differentiation and integration, as well as the treatment of ordinary differential equations. This is extended by a brief introduction to thenumerics of partial differential equations. The second part deals with the generation of random numbers,summarizes the basics of stochastics, and subsequently introduces Monte-Carlo (MC) methods. Specificemphasis is on MARKOV chain MC algorithms. The final two chapters discuss data analysis and stochasticoptimization. All this is again motivated and augmented by applications from physics. In addition, the bookoffers a number of appendices to provide the reader with information on topics not discussed in the main text. Numerous problems with worked-out solutions, chapter introductions and summaries, together with a clearand application-oriented style support the reader. Ready to use C++ codes are provided online. 428 pp. Englisch. Seller Inventory # 9783319272634
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